tbuckley/cabot-search huggingface dataset:
Absence of CD4<sup>+</sup> and CD8<sup>+</sup> T cell expansion after primary multimodal treatment predicts early progression in inoperable stage III NSCLC.
Authors: Thomas Philipp Hofer, Alexander Nieto, Lukas Käsmann, Julian Taugner, Carolyn Pelikan, Dinar Katanov, Chukwuka Eze, Julian Guggenberger, Claus Belka, Elfriede Noessner, Farkhad Manapov
Journal: Journal of Clinical Oncology (2022)

e20590 Background: There are no blood-based biomarkers for survival prediction in inoperable stage III NSCLC patients. We propose a method for calculation of novel area under curve (AUC) biomarkers of the dynamic change of multiple leukocyte subpopulations before, during, and after thoracic irradiation (TRT), chemoradiotherapy (CRT), and chemo-radio-immunotherapy (CRT-ICI) in this patient cohort. The extracted biomarkers identify patients with early progression after TRT. Methods: 20 patients (17 male, 3 female), at median age of 65.5 years (range 34 to 79) were enrolled in the study. The median follow-up time was 60 weeks. Eleven patients suffered from adenocarcinoma, 8 squamous cell carcinoma, and 1 undifferentiated NSCLC. They received TRT (2/20, 10%), CRT (11/20, 55%), or CRT-ICI (7/20, 35%). One patient (1/20, 5%) withdrew consent and was excluded from analysis. Primary endpoints were progression free survival (PFS) at 6 and 12 months. Patient blood was analyzed via flow cytometry for 7 circulating leukocyte populations at baseline, twice during radiotherapy, at the end of radiotherapy (RTend), and 10, 20, 35, 48, and 60 weeks after enrollment. We analyzed CD3 + total T cells, CD4 + T cells, CD8 + T cells, CD19+/CD20 + B cells, CD3 - CD56 + NK cells, CD56 bright NK cells, and CD56 dim NK cells. Here, we report on CD4 + and CD8 + T cells. The AUC from RTend to zenith of absolute cell counts provided aggregate measures for the time-course data. We performed hierarchical clustering and cluster characterization. Relevant features were selected by stepwise drop-out. Results: Clustering of the AUC between RTend and zenith for CD4 + T cells and CD8 + T cells delineated two prognostic groups. The favorable group was characterized by higher AUC values for CD4 + and CD8 + T cells compared to the unfavorable group. All patients (9/9, 100%) in the favorable group versus 36.4% (4/11) patients in the unfavorable group were progression-free at 6 months (Fisher´s exact test, two-tailed: p-value = 0.00472). This effect was observed as a trend with PFS at 12 months. Here 66.6% (6/9) of patients had PFS at 12 months in the favorable group versus 27.3% (3/11) in the unfavorable group (Fisher´s exact test, two-tailed: p-value = 0.175). There is a directly proportional relationship of the reported AUC values to PFS at 6 months and 12 months. Conclusions: Patients who responded with T cell expansion after immunogenic cell death by TRT, CRT, or CRT-ICI had significantly longer PFS compared to those without increase. Longitudinal monitoring of CD4 + and CD8 + T cells and the AUC from RTend to zenith is a promising biomarker for detecting early progression in the present study which is the subject of validation in an ongoing prospective study (PRECISION, NCT05027165).
Predictors of adjuvant chemotherapy refusal in lung cancer: A National Cancer Database Study.
Authors: Anjan Katel, Rebecca A. Nelson, Ranjan Pathak
Journal: Journal of Clinical Oncology (2022)

8521 Background: Adjuvant chemotherapy (AC) have been shown to improve overall survival in non-small cell lung cancer (NSCLC). Despite showing significant survival benefit across various age groups, patients are known to refuse AC. However, the factors associated with such a decision remain poorly understood in lung cancer. We therefore sought to investigate the factors associated with AC refusal in a nationally representative database in the United States (US). Methods: From 2004 to 2017, adults (≥20 years) with histologically confirmed non-small cell lung cancer (NSCLC) who underwent complete resection and were deemed to be chemotherapy eligible (node-positive or size ≥5 cm) were identified in the National Cancer Database (NCDB). Annual trends and factors associated with refusal of AC in chemotherapy-eligible NSCLC patients were evaluated using Joinpoint regression and multivariable logistic regression. Results: Among the 44,957 patients who met the inclusion criteria, 18,468 (3,678 (8.2%)) were noted to refuse chemotherapy in the NCDB. Patients refusing adjuvant chemotherapy were more likely to be elderly (OR 1.08, 95% CI, 1.07-1.08; P&lt;.001), uninsured when compared with government insurance (OR 1.79, 95% CI, 1.38-2.33; P&lt;.001), treated in the Western region of the when compared with patients in the Northeast (OR 1.47, 95% CI, 1.28-1.68; P&lt;.001). They were also more likely to have a higher Charlson score versus patients with Charlson score of zero (OR 1.31, 95% CI, 1.18-1.46; P&lt;.001), have squamous cell carcinoma versus adenocarcinoma (OR 1.20, 95% CI, 1.11-1.31; P&lt;.001), undergo pneumonectomy versus lobectomy (OR 1.31, 95% CI, 1.16-1.47, P&lt;.001), and have ≥2 weeks hospital length of stay versus &lt; 2 weeks (OR 2.25, 95% CI, 1.93-2.63; P&lt;.001). Conclusions: In our analysis, we identified several sociodemographic and clinicopathologic variables that were independently associated with chemotherapy refusal. We saw the number of patients refusing AC increased sharply during the study period. Our study shows that in addition to poor post-operative recovery, underlying sociodemographic factors might predict patients at risk for refusing adjuvant chemotherapy in lung cancer. Further understanding of these factors might help devise effective interventions to motivate patients to undergo potentially life-extending chemotherapy in lung cancer.
Cancer care for the poor-health system augmentation model.
Authors: Dinesh Pendharkar, Chandramauli Tripathi
Journal: Journal of Clinical Oncology (2022)

e13514 Background: Access to cancer care is well recognized issue. It has many elements, mainly- social inequity, financial, distance to care centers, health behavior etc. These challenges increase with the level of poverty in LMIC. Models of peripheral empowerment, cost reduction, creation of alternate workforce, bending of health systems to include cancer care as a stream are important. Here we report incorporation of cancer vertical in to existing health care delivery models of India (Pendharkar model). Methods: Health care to major population is provided through government lead systems of primary health care centers, merging at district administrative level in to district hospitals. As per various WHO mandates the focus had been on general medicine, surgery, maternal and child health. Through advocacy a parallel vertical of cancer care delivery was initiated, creating “district cancer program” with written down organizational, functional and financial structure. Starting from one state it was expanded to many states. Results: Initiation and launch of district cancer care program has revolutionized cancer care at state level. One medical officer was designated as district cancer nodal officer. He was trained and given physical identity with creation of cancer unit with patient beds, and capacity of performing procedures including chemotherapy. Paramedical personnel and nurses were attached to this unit and trained. Drug formulary of the state was changed with addition of anticancer drugs in to the list. Procurement process at state level was started and units were equipped with anticancer drug bank. Cancer officers were mandated to play various roles like-assist in cancer patients’ journey- from diagnostics to end of life care offering free chemotherapy and palliative care, creating registry, public awareness and professional awareness, assisting in cancer screening programs. The program completing 8 years, has been initiated in 8 states, with nearly 200 districts trained. Five states have formalized it by state notifications issuing operational guidelines with pan state coverage, as a vertical program. Few hundred patients are helped on daily basis. Conclusions: Reduction in cancer care gap can be achieved using existing widespread government health system, by creating vertical cancer program in existing structure. It can be facilitated by utilizing existing resources, capacity building of alternate oncology workforce, mandating health system to take care of cancer patients at affordable cost. [Table: see text]
High exosomal PD-L1 expression in relation to lymph node progression in metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone (abi) or enzalutamide (enza).
Authors: Vincenza Conteduca, Marzia Del Re, Emanuela Scarpi, Stefania Crucitta, Giorgia Gurioli, Giuliana Restante, Federico Cucchiara, Cristian Lolli, Nicole Brighi, Giuseppe Schepisi, Chiara Casadei, Paola Ulivi, Himisha Beltran, Romano Danesi, Ugo De Giorgi
Journal: Journal of Clinical Oncology (2022)

e17038 Background: Programmed death-ligand 1 (PD-L1) has been recently found in tumor-derived exosomes and associated with progressive disease (PD) ( Poggio, Cell 2019). In localized prostate cancer, PD-L1 tumor expression has been shown to be a biomarker for node-positive patients (pts) ( Petitprez, Eur Urol Focus 2019) but its role in mCRPC is largely unexplored. We aimed to determine the potential of PD-L1 exosomal expression to predict lymph nodal PD in mCRPC receiving abi or enza. Methods: In a biomarker prospective study (REC 2192/2013), exosomes were isolated from plasma samples collected before first-line therapy with abi/enza between December 2014 and October 2018. RNA was extracted for analysis of PD-L1 by digital droplet PCR ( Del Re, Prostate Cancer Prostatic Dis 2021). Results: In our cohort of 55 node-positive mCRPC pts (median age: 76 years, range 47-89), the amount of exosomal PD-L1 expression (pts dichotomized in “high” and “low” as below or above median PD-L1/ACTB ratio = 0.0052) was associated with radiographic response after the first 3 months abi/enza therapy [high PD-L1 vs low PD-L1: 8 (25.8%) vs 0 (0%) PD, 23 (74.2%) vs 18 (75%) stable disease, and 0 vs 6 (25%) partial/complete response] (p = 0.0009). We observed an overall median progression-free survival (PFS) of 14.3 months [95% confidence interval (CI) 8.6-not reached] shorter in high PD-L1 compared to low PD-L1 10.6 (6.5-23.4) vs not reached [hazard ratio (HR) 3.1 (95% CI 1.1-8.5), p = 0.023]. In multivariable analysis including exosomal PD-L1 and androgen receptor (AR) variant 7, AR copy number gain detected in plasma, neutrophil lymphocyte ratio (NLR), lactate dehydrogenase, exosomal PD-L1; AR-V7 and AR gain were independent predictors of nodal PFS (HR 5.8, 95% CI 1.4-24.2, p = 0.01, HR 3.2, 95% CI 1.1-9.2, p = 0.03 and HR 12.9, 95% CI 2.3-73.2, p = 0.004), whereas AR-V7, AR gain, NLR &gt; 3 were independent predictors of OS (HR 4.9, 95% CI 1.8-13.1, p = 0.001, HR 4.4, 95% CI 1.1-17, p = 0.02, and HR 3.2 95% CI 1.1-9.4, p = 0.03, respectively). Moreover, a trend of a worse OS was reported in high PD-L1 compared to low PD-L1 pts (HR 2.6, 95% CI 0.9-7.5, p = 0.07). Conclusions: In mCRPC pts treated with ARSI, exosomal PD-L1 expression may be considered as a predictive biomarker of lymph nodal response, playing a potential role in individualized disease monitoring and treatment combining between ARSI and immunotherapy. Larger evaluation of treatment decisions based on exosomal PD-L1 expression is now required.
A phase II study of anlotinib combined with temozolomide in the treatment of patients with recurrent glioblastoma.
Authors: Qingsheng Xu, Qun Chen, Xiujue Zheng, Jinquan Cai, Renya Zhan
Journal: Journal of Clinical Oncology (2022)

e14021 Background: Glioblastoma (GBM) is a highly vascularized tumor and there are few treatment options after disease recurrence. This study assessed the efficacy and safety of anlotinib, a multitarget tyrosine kinase inhibitor, combined with temozolomide in the treatment of these patients. Methods: This is an open-label, single-arm, phase II trial (ChiCTR2000028957). Patients with histologically confirmed GBM with definite progression after surgery followed by radiotherapy and temozolomide chemotherapy were eligible for inclusion. Additional inclusion criteria were 1) 18-70 years old, 2) KPS≥60, 3) disease progression on MRI as defined by Response Assessment in Neuro-Oncology (RANO) criteria at least 12 weeks (wks) after completion of radiotherapy，4) antiangiogenic therapy naïve. All patients received temozolomide (150-200mg/m 2 , orally, QD, d1-5/4wks) and anlotinib (10mg, orally, QD, d1-14/3wks) until disease progression or unacceptable toxicity. The primary endpoint was objective response rate (ORR, defined as partial and complete responses according to RANO criteria). Safety assessment was done in patients who received at least one dose of study agent. Results: Twenty-one patients (9 males and 12 females) were enrolled between May 2020 and July 2021, and the median age is 55 (range 27-68) years old. Molecular pathological types included MGMT promoter methylated (n = 5), IDH mutation (n = 5), 1p/19q codeletion (n = 8), and TERT promoter mutation (n = 12). Analyses included data collected through December 15, 2021. Tumor response occurred in 17 patients, of which 9 patients had a complete response, and ORR was 81.0% (17/21). There were also 3 patients achieved stable disease and the disease control rate was 95.2% (20/21). Median progression-free survival (PFS) was 13.2 months [95%CI 3.90-22.52], and the PFS at 6 months was 60.0%. The incidence of adverse events of grade 3 was 28.6%, with a higher incidence of elevated AST (25.0%) and ALT (20.0%), hypertension (16.7%), leukopenia (15.4%). No grade 4 or treatment related death occurred in this study through the follow-up. Overall, toxicities are mild and manageable. Conclusions: Anlotinib combined with temozolomide is efficacious and well-tolerated in recurrent GBM patients. Clinical trial information: ChiCTR2000028957.
Depression trajectories among women undergoing chemotherapy.
Authors: Johanna A. Suskin, Steven M Paul, Ashley Stuckey, Christine Miaskowski, Laura B. Dunn
Journal: Journal of Clinical Oncology (2022)

e24144 Background: Depressive symptoms are common among women undergoing chemotherapy (CTX) for breast or gynecological cancer. Many studies have examined the prevalence of depressive symptoms (usually at the beginning or end of CTX). However, given that CTX unfolds over a number of cycles, there is a need to better understand patterns of change in depressive symptoms over the course of treatment, and to identify factors that may predispose individuals to worse symptom trajectories. The purpose of this study, among women who underwent CTX for breast or gynecological cancer, was to evaluate for interindividual differences in depressive symptoms over the course of two cycles of CTX, and to identify characteristics associated with both initial levels (i.e., at the beginning of the study) and trajectories of depressive symptoms. Methods: Patients undergoing CTX for breast (n = 530) or gynecologic (n = 233) cancer completed the Center for Epidemiological Studies-Depression (CES-D) questionnaire six times over two treatment cycles. Patient-reported measures were used to assess demographic, clinical, symptom, stress, and coping characteristics at enrollment. Using hierarchical linear modeling (HLM), we evaluated characteristics associated with initial levels and trajectories of depressive symptoms. Results: One demographic (marital status) and two clinical (number of comorbidities, functional status) characteristics predicted interindividual differences in initial levels of depressive symptoms. One demographic (education) and one clinical (MAX-2 score, a CTX toxicity metric) characteristic were associated with interindividual differences in depressive symptom trajectories. Several symptom characteristics predicted interindividual differences in initial levels (i.e., morning fatigue), trajectories (i.e., initial level of depression), or both initial levels and trajectories (i.e., sleep disturbance, attentional function) of depressive symptoms. Two stress-related variables (i.e., perceived stress, cancer-related distress) predicted interindividual differences in both initial levels and trajectories of depressive symptoms. Several coping variables predicted interindividual differences in initial levels (i.e., behavioral disengagement), trajectories (i.e., venting), or both initial levels and trajectories (i.e., self-blame) of depressive symptoms. Conclusions: The range of demographic, clinical, symptom, stress and coping characteristics associated with interindividual differences in depressive symptoms underscores the importance of evaluating risk and protective factors. These factors may serve as useful markers for both screening and intervention to address depressive symptoms during CTX.
Incorporating patient-reported outcome data into a hematopoietic cell transplant survival calculator.
Authors: Bronwen E. Shaw, Kathryn E. Flynn, Rachel Cusatis, Anita D'Souza, Betty Ky Hamilton, Mary M. Horowitz, Deborah Mattila, Rachel Phelan, Stephanie Lee, Ruta Brazauskas
Journal: Journal of Clinical Oncology (2022)

7045 Background: The Center for International Blood and Marrow Transplant Research (CIBMTR) provides a validated 1-year Overall Survival (OS) calculator to estimate outcomes for individual patients prior to allogeneic Hematopoietic Cell Transplant (HCT) to inform risk. The calculator considers pre-HCT clinical and demographic characteristics, but not patient-reported outcome (PRO)s. Pre-HCT PRO scores have been associated with OS. We hypothesized that adding the baseline PRO score to the calculator will enhance its performance in predicting OS. Methods: In addition to established covariates,we considered pre-HCT PRO scores, collected on five (published) prospective randomized clinical trials performed through the Blood and Marrow Transplant Clinical Trials Network (BMT CTN). Measures used were the SF36 physical component score (PCS) and mental component score (MCS), and the FACT-BMT Trial outcome index (TOI). We also investigated inclusion of a single question from the SF36: In general, would you say your health is: excellent/very good/good vs fair/poor. Patients were ≥18. Results: 1,033 patients were included, 341 (33%) completed only the SF36, 339 (33%) only the FACT-BMT and 353 (34%) both, per study design. HCT occurred 2004-2014, and the population was diverse with respect to disease, stage, demographics, and transplant characteristics. When adjusted for clinical characteristics, the PCS was significantly predictive of mortality (HR=0.88, 95%CI 0.81-0.96, p=0.0021), while the MCS and TOI were not. The single general health question was also significantly associated with mortality (HR=0.52, 95%CI 0.35-0.74, p=0.0004). Addition of PRO scores to the calculator did not result in a significant change in the model’s predictive ability as measured by Harrell’s concordance statistic (Table). Conclusions: In this large analysis, we confirmed the significant, independent association of pre-HCT PRO scores with OS. We showed, for the first time in this setting, that a single general health question is as accurate as the full SF36 measure for predicting survival, but we did not find support for the hypothesis that adding PROs to the calculator improved its performance. Estimates of baseline PRO measure effect on mortality and model concordance statistics at 1-year post-HCT. [Table: see text]
Cisplatin-induced nephrotoxicity in hyperthermic intraperitoneal chemotherapy (HIPEC) is mitigated by sodium thiosulfate: Clinical and toxicotranscriptomic results of a prospective trial.
Authors: Nicole Lugo Santiago, Ernest Soyoung Han, Mustafa Raoof, Xiwei Wu, Hyejin Cho, Stephen Lee, Wei-Chien Lin, Jeff Feng-Hsu Lin, Daphne B. Stewart, Nora H. Ruel, Edward Wenge Wang, Isaac Benjamin Paz, Mark Tsuneo Wakabayashi, Lorna Rodriguez-Rodriguez, Mihaela C. Cristea, Thanh Hue Dellinger
Journal: Journal of Clinical Oncology (2022)

5570 Background: Hyperthermic intraperitoneal chemotherapy (HIPEC) with cisplatin confers a survival benefit in epithelial ovarian cancer (EOC). Unfortunately, cisplatin is associated with significant renal toxicities. Sodium thiosulfate (ST) has been suggested as a nephroprotectant for patients undergoing HIPEC with cisplatin. Methods: A feasibility trial ( ClinicalTrials.gov: NCT01970722) evaluated safety outcomes of HIPEC with cisplatin 75 mg/m 2 during optimal cytoreductive surgery (CRS) in patients with EOC and endometrial cancer (n = 40), with or without ST. Twenty-one patients received no sodium-thiosulfate (nST group), and nineteen patients received sodium thiosulfate (ST group). Toxicities were reported according to CTCAE v. 5. Progression-free survival was followed. Normal tissue biopsies were collected intra-operatively immediately following HIPEC and cisplatin exposure in a subset of patients (n = 21), and profiled with transcriptomic sequencing to identify RNAseq signatures correlating with toxicities. Hierarchical cluster analyses identified distinct transcriptomic signatures in post-HIPEC normal samples of patients with renal AEs (rAEs) compared to no renal AEs (nrAEs). KEGG pathway analysis identified up- or downregulated gene sets using GSEA. Results: Forty patients had HIPEC at time of optimal CRS. Renal toxicities were higher in the nST group (no sodium thiosulfate) compared to the ST group. nST patients had 17% any grade, and 9% Grade 3 AEs for acute and chronic kidney injuries. In contrast, ST patients suffered 0% renal AEs. rAE patients demonstrated upregulation of immune signaling pathways (Toll-like receptor, Natural killer cell, Nod-like receptor); and downregulation of metabolic pathways. Top upregulated genes in rAE patients included immune (e.g. neutrophil) related genes, while downregulated genes included metabolism genes. Kaplan-Meier curves demonstrated improved PFS in primary ovarian cancer patients undergoing HIPEC who were treated with ST vs no ST (p = 0.04, NR vs 13.4 mo). Conclusions: HIPEC with cisplatin results in significant renal toxicities. The mechanisms of cisplatin-induced nephrotoxicity in HIPEC are immune-related and reflect reduced metabolism. Sodium thiosulfate abrogated renal toxicities and did not decrease PFS. Clinical trial information: NCT01970722.